Absence of Persistent Hepatitis E Virus Infection in Antibody-Deficient Patients Is Associated With Transfer of Antigen-Neutralizing Antibodies From Immunoglobulin Products
Bibliographic record
Abstract
Background: Persistent hepatitis E virus (HEV) infection is described in a number of immunosuppressive conditions. We aimed to determine the risk of persistent HEV infection in patients with primary or secondary antibody deficiency. Methods: Two hundred forty-five antibody-deficient patients receiving regular immunoglobulin replacement therapy were tested for HEV RNA and anti-HEV immunoglobulin G (IgG). Immunoglobulin products and plasma specimens obtained from 9 antibody-deficient patients before and after intravenous immunoglobulin (IVIG) therapy, 5 recently treated patients with persistent HEV infection, and 5 healthy patients recovered from acute HEV infection were analyzed for anti-HEV IgG and for antibody reacting with HEV antigen. Results: No antibody-deficient patient had detectable plasma HEV RNA. Anti-HEV IgG was detected in 38.8% of patients. All 10 immunoglobulin products tested contained anti-HEV capable of neutralizing HEV antigen. Plasma samples collected following IVIG infusion therapy demonstrated a higher anti-HEV IgG level and neutralizing activity, compared with samples collected before IVIG therapy. Neutralizing activity was similar to that in healthy patients with recent acute HEV infection. Conclusion: The risk of persistent HEV infection in patients with antibody deficiency appears extremely low. This may be due to passive seroprotection afforded by the ubiquitous presence of anti-HEV in immunoglobulin replacement products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".